7 papers
Restoring Linguistic Grounding in VLA Models via Train-Free Attention Recalibration
Ninghao Zhang, Bin Zhu, Shijie Zhou +1
Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasingly viewed as a foundation for generali…
Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs
Zeyi Huang, Yuyang Ji, Xiaofang Wang +11
Long-form video understanding with Large Vision Language Models is challenged by the need to analyze temporally dispersed yet spatially concentrated key moments within limited cont…
Switchable Activation Networks
Laha Ale, Ning Zhang, Scott A. King +1
Deep neural networks, and more recently large-scale generative models such as large language models (LLMs) and large vision-action models (LVAs), achieve remarkable performance acr…
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Orr Zohar, Xiaohan Wang, Yann Dubois +9
Despite the rapid integration of video perception capabilities into Large Multimodal Models (LMMs), the underlying mechanisms driving their video understanding remain poorly unders…
Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction
Shiyu Zhao, Zhenting Wang, Felix Juefei-Xu +7
Prevailing Multimodal Large Language Models (MLLMs) encode the input image(s) as vision tokens and feed them into the language backbone, similar to how Large Language Models (LLMs)…
Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation
Bolin Lai, Felix Juefei-Xu, Miao Liu +8
Text-guided image manipulation has experienced notable advancement in recent years. In order to mitigate linguistic ambiguity, few-shot learning with visual examples has been appli…